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EChuck McLeesterVisit Author's PageChuck McLeester's blog explores issues about marketing and marketing measurement. He is a marketing strategist and analyst with experience in healthcare, pharmaceuticals, financial services, pet products, travel/hospitality, publishing and other categories. He spent several years as a client-side direct marketer and 25 years on the agency side developing expertise in direct, digital, and relationship marketing. Now he consults with marketers and advertising agencies to create measurable marketing programs.

ETTom SmithVisit Author's PageTom Smith is a DZone research analyst who built a career gathering insights from analytics to inform integrated marketing plans that make a significant positive impact on business. He's a hands-on leader in marketing and analysis who has worked with more than 120 clients in eight vertical industries. Smith is an experienced full-stack marketer who uses insights to drive positioning and branding, demand generation and lead creation, channel management, and customer relationship management and customer experience. The purpose of his blog is to share thought-provoking insights regarding customer experience. Reach him at tctsmithiii@gmail.com.

What should Donald Trump Jr. and Eric Trump do with Trump Brand? The brand has traditionally been positioned as upscale: hotel rooms that start at $400; golf club memberships for up to $200,000; $50 cologne; $40 wines; $175 ties. But with the president’s low approval ratings, things have not gone well in some of the Trump businesses — paving the way for some geo-demographic segmentation opportunities.

It's hard to believe that just a decade ago, the only way to process and analyze large data sets involved manipulating and querying relational database management systems (RDBMS). Database professionals served as gatekeepers of this information, and data was structured in columns and rows—with subsequent data input having to conform to this schema to be stored. And though the data explosion was still years away, managing structured data was already pushing the limits of available hardware, forcing enterprises to make expensive capital expenditures on supporting technology.